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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/141552


    Title: 新多元變異係數定義與其對應之管制圖
    A New Definition of Multivariate Coefficient of Variation and Its Corresponding Control Charts
    Authors: 潘維辰
    Pan, Wei-Chen
    Contributors: 楊素芬
    葉百堯
    蕭又新
    Yang, Su-Fen
    Yeh, Bai-Yau
    Shiau, Yuo-Hsien
    潘維辰
    Pan, Wei-Chen
    Keywords: 向量化變異係數
    多元指數加權移動平均
    平均連串長度
    多元變異係數
    管制圖
    Average run length
    Control chart
    Multivariate coefficient of variation
    Multivariate exponentially moving average
    Vectorized coefficient of variation
    Date: 2022
    Issue Date: 2022-09-02 14:46:53 (UTC+8)
    Abstract: 傳統上，我們經常使用舒華特管制圖監控製程的平均數及變異數，即使在此之後有許多效果卓越的改良，但我們通常是將平均數即變異數分開監控，因此在某些臨床醫學或工業領域中，當我們希望監控的是製程變異係數(CV)時，傳統的平均數及變異數將不再適用，CV管制圖即是為了解決此問題而被提出。

    多元統計製程控制在近年日趨熱門，多元變異係數(MCV)管制圖也隨之誕生，然而，在現有的發展下，MCV管制圖中對於MCV統計量的定義對於單維度的CV偏移是不敏感的，因此我們嘗試使用向量化變異係數 (vectorized coefficient of variation, VCV)來建立管制圖並監控多元製程變量下的CV以得到更好的改善，我們也同時提出了多元指數加權移動平均(MEWMA)型VCV管制圖，並使用製程失控時的平均連串長度來進行偵測性能的測量，在本研究中已證實MEWMA型VCV管制圖可超越初始的舒華特型VCV管制圖，並且也優於現有在MCV定義下的管制圖。此外，本研究中展示了關於相關係數的偏移在VCV管制圖和MCV管制圖之間行為，最後使用兩不同分配之半導體數據說明VCV管制圖的實務應用。
    In some clinical or industrial applications, it is critically important to monitor the process coefficient of variation (CV). Though there are many existing control charts for monitoring either process mean or variance, the conventional Shewhart X ̅-chart and R-chart (or S-chart) cannot deal with the setting of constant CV. Therefore, the CV control chart is proposed for dealing this problem.

    In recent years, there has been a resurgent interest in developing multivariate statistical process control (MSPC) charts. The multivariate coefficient of variation (MCV) control chart was soon proposed and has been further discussed. However, the existing MCV charts are not sensitive to CV changes which occur at individual variables. In this study, we propose a new definition of multivariate CV, the vectorized CV (VCV), to better capture more subtle changes in CV in individual variables. The multivariate exponential weighted moving average (MEWMA) type VCV control chart is also proposed and has been demonstrated to improve the Shewhart-type VCV chart in this study. The average run length (ARL) is used for the performance measurement. It is shown that the proposed VCV based control charts outperform the existing MCV charts, especially with regards to the MEWMA type VCV chart. Furthermore, the cases when only correlation changes are evaluated and compared between the VCV charts and the MCV charts. A multivariate normal process example and a multivariate non-normal process example are presented to show how the proposed charts can be applied in practice.
    Reference: Amdouni, A., Castagliola, P., Taleb, H., & Celano, G. (2016). One-sided run rules control charts for monitoring the coefficient of variation in short production runs. European Journal of Industrial Engineering, 10(5), 639-663.
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    Description: 碩士
    國立政治大學
    統計學系
    109354025
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0109354025
    Data Type: thesis
    DOI: 10.6814/NCCU202201231
    Appears in Collections:[Department of Statistics] Theses

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